CN114676590A - Simulation model for individual decision - Google Patents

Abstract

The invention relates to the technical field of individual decision simulation models, in particular to an individual decision simulation model, which adopts modularized program design and comprises a behavior module, an individual module, a government module, a decision module, a main function module, a file management module and an interface module.

Description

A Simulation Model of Individual Decision-Making

technical field

The invention relates to the technical field of individual decision-making simulation models, in particular to a simulation model of individual decision-making.

Background technique

The agro-environmental system is an open and complex adaptive system that involves not only the physical characteristics of the environment itself, but also the complex interaction between the economy, society and the ecological environment. This complex interaction largely originates from the participants with different characteristics in the system, such as individual farmers, enterprises, and governments. These subjects have different decision-making and behavioral principles, and take adaptive measures of continuous learning with the development of technology and the transmission of information. Under different temporal and spatial conditions, the main body interacts with different environmental systems in different dimensions and to different degrees, which makes the agricultural system show the characteristics of adaptability, evolution, nonlinearity and non-equilibrium. The agent-based modeling method is based on the theory of complex adaptive systems. With the help of interdisciplinary and advanced computer technology, the interaction of heterogeneous agents in various environmental systems can be well described. By setting different rules and mechanisms, Deeply characterize nonlinear relationships in systems. The agent-based modeling method can integrate traditional research methods, overcome the limitations of traditional methods for modeling complex system problems, help people understand and solve various complex system problems, and better assist people in decision-making.

As early as the late 1990s, some researchers began to use simulation models to study the decision-making process of farmers. The most classic model is the AGRIPOLIS model designed by Balmann et al. Impact. After that, Lobianco optimized on the basis of the AGRIPOLIS model and designed the RegMAS model, which provided ideas for the solution of production decision-making problems in the agricultural field.

However, these models make decisions for specific problems in a single field of agriculture and lack universality. Decision-making problems in actual situations spread across all walks of life, the decision-making environment is complex and diverse, and there are many related influencing factors, which limit the application of this type of simulation model.

Therefore, it is necessary to design a simulation model of individual decision-making. By setting a series of external resource and environmental conditions and individual resource endowments, the method of mathematical programming is used to simulate the decision-making of actors to maximize their own utility or profit under resource constraints. Behavior.

SUMMARY OF THE INVENTION

The purpose of the present invention is to overcome the deficiencies of the prior art and provide a simulation model for individual decision-making. By setting a series of external resource environment conditions and individual resource endowments, the method of mathematical programming is used to simulate the behavior of the main body under resource constraints. Conditional decision-making behavior to maximize its own utility or profit.

In order to achieve the above object, the present invention provides a simulation model of individual decision-making, the model adopts modular program design, including behavior module, individual module, government module, decision-making module, main function module, file management module and interface module;

[Behavior module]: The model obtains all production behaviors by reading the production input and output files, and constructs each behavior object through the behavior module. These behavior objects will be instantiated and called in the optimization decision module ;

[Individual module]: The model obtains all individuals and their basic attributes by reading the individual basic attribute file, and constructs each individual object from these individuals through the individual module. These individual objects will be instantiated in the optimization decision module and created. is called;

[Government Module]: The model reads government subsidy files and policy category parameters, and constructs government objects in the government module. At the same time, it completes the settings of subsidy methods, subsidy standards and demonstration individuals. The government objects will be instantiated in the optimization decision module and created. is called;

[Decision module]: This module calculates the decision result of each individual by setting a set of unified action criteria for each individual and introducing the idea of linear programming into the model, that is, the method of solving the optimal solution of the objective function under the constraints. ;

[Main function module]: This module is the entry point for the model to run and is responsible for

Initialize the basic variables before the model runs, including control file variables, input and output file variables, and log file variables;

Execute the simulation of each period in a loop, receive the simulation results of the previous period and pass them into the simulation of the next period;

Release the buffer and temporary files, save the program running log, and print the model running end information;

[File management module]: This module realizes the reading of all input files and control files. The model supports data files in xls, xlsx format and control files in txt format. This module is responsible for reading these data files and storing them in temporary In the buffer, when other modules need to obtain data, the file management module will query the temporary buffer, find the corresponding data and pass it to these modules;

[Interface module]: This module implements the loading of external link libraries. The model needs to call external operation libraries when calculating individual optimal decisions. These operation libraries cannot be directly connected to the model itself. The interface module constructs general access rules. The external library can be compatible with the model through the interface module, which is convenient for the expansion of the model;

The connection between the modules is as follows:

The decision-making module depends on the behavior module, the individual module and the government module, and the external library provides functional expansion support for the optimization module through the interface module;

The file management module is connected with the behavior module, the individual module and the government module, and the data transmission behavior module is aggregated in the individual module to realize the correspondence between the behavior and the individual;

The individual module is linked with the government module, and individual decision-making is subject to the government module's setting of the policy environment;

A. All other modules are aggregated into the main function, which together constitute the architecture of the entire model.

The objective functions in the decision module include:

【Profit income】: The profit function consists of total revenue minus total cost plus government subsidies and other revenue components;

Profit _t =Total Revenue-Total Cost+Subsidies+Other Income

It is formulated as: maxП _t =TR _t -TC _t +Sub _t +OI _t

[Total revenue]: The total revenue TR _t is measured by the product of the output Q _t of all products produced in the year and the price P _t : TR _t = Q _t P _t

[Total cost]: The total cost TC _t includes the total variable cost VC _t and the total fixed cost FC _t ;

Calculated using the input-output method, that is, the product of output _xi , input-output coefficient a _ij and factor price p _j to measure the current variable cost:

The total fixed cost refers to fixed assets such as factory buildings, machinery and equipment. This production factor is invested in one time and used in multiple periods. The cost calculation method is discounted to each year of the service life according to the total value of the purchase period, and the fixed asset purchase period is set. The total value is Fixed asset, the annual discount rate is r, and the service life is T, then the annual discounted cost of fixed assets is:

[Government subsidy]: There are two calculation forms for government subsidy Subsidies. When subsidy is made according to the results of production behavior, Sub ^out is the product of the change in the results of the out ^report during the project reporting period and the out ^base in the base period and the amount of subsidies; If the technology adoption is subsidized, Sub ^adoption calculates the product of adoption and subsidies:

Subb ^out =subsidies*(out ^report -out ^base )

[Other income]: Other income is income other than production, expressed as the product of total labor OL _t and wage amount w _t : OI _t = OL _t w _t

To sum up, the objective function of individual profit maximization can be expressed as:

The constraints in the decision module are:

[Budget Constraint]: The budget constraint is that the individual sets a budget value in advance for the current year. The total production cost of the current year should be controlled within the budget value, including variable costs and fixed costs. The budget for each year is equal to the previous year's budget. Part of the total profit:

【Endowment Constraint】: Endowment constraint is the means of production such as labor, machinery, land, etc. that are owned by the individual before the individual production begins. Let the initial endowment of each production factor of the individual be b _j , and b _j refers to the jth production factor , then the usage of each factor of production should be less than its endowment:

The specific process of the decision-making module is: the model reads the resource endowment file, production input and output file, and product price file of the behavior module, obtains the input-output coefficient of each production behavior, the resource endowment and product price of all individuals, and then calls the individual The module instantiates all individuals, calls the government module to instantiate the current policy environment, constructs the policy environment and resource endowment conditions for each individual's production decision, and defines the unified production goal of each individual, and finally imports these individuals into the linear programming function Calculate and output their optimal production behavior results in turn.

Compared with the prior art, the present invention adopts modular program design, including behavior module, individual module, government module, optimization decision module, main function module, file management module and interface module. -based modelling, ABM) ideas and norms, suitable for the study of individual decision-making behavior in multi-agent systems.

Description of drawings

Fig. 1 is a schematic diagram of a model running process flow of the present invention;

Fig. 2 is the standard modeling schematic diagram of the present invention;

3 is a display diagram of the control.properties interface according to an embodiment of the present invention;

4 is a display diagram of a data01 folder interface according to an embodiment of the present invention;

Fig. 5 is the farm_endowment.csv file interface display diagram of the embodiment of the present invention;

Fig. 6 is the input_output_tradition.csv file interface display diagram of the embodiment of the present invention;

7 is a display diagram of an input_output_deep.csv file interface according to an embodiment of the present invention;

FIG. 8 is a display diagram of the input_output_slow.csv file interface according to an embodiment of the present invention;

Fig. 9 is the farm_parameters.csv file interface display diagram of the embodiment of the present invention;

Fig. 10 is the carbon_price.csv" file interface display diagram of the embodiment of the present invention;

FIG. 11 is an interface display diagram of the “activity_price.csv” file according to an embodiment of the present invention;

FIG. 12 is a display diagram of a subsidy.csv file interface according to an embodiment of the present invention;

Fig. 13 is the carbon_reduce.csv file interface display diagram of the embodiment of the present invention;

FIG. 14 is a display diagram of an operation result using a traditional fertilization technique according to an embodiment of the present invention;

Fig. 15 is the operation result display diagram of adopting slow-release fertilizer technology according to the embodiment of the present invention;

Fig. 16 is the operation result display diagram of adopting the deep application technology of chemical fertilizer according to the embodiment of the present invention;

17 is a display diagram of the “result_5.csv” file interface according to an embodiment of the present invention;

Detailed ways

The present invention will now be further described with reference to the accompanying drawings.

The present invention provides a simulation model for individual decision-making:

As shown in Figure 1 to Figure 17, the model adopts modular program design, including behavior module, individual module, government module, decision-making module, main function module, file management module and interface module;

[Behavior module]: The model obtains all production behaviors by reading the production input and output files, and constructs each behavior object through the behavior module. These behavior objects will be instantiated and called in the optimization decision module ;

[Individual module]: The model obtains all individuals and their basic attributes by reading the individual basic attribute file, and constructs each individual object from these individuals through the individual module. These individual objects will be instantiated in the optimization decision module and created. is called;

[Government Module]: The model reads government subsidy files and policy category parameters, and constructs government objects in the government module. At the same time, it completes the settings of subsidy methods, subsidy standards and demonstration individuals. The government objects will be instantiated in the optimization decision module and created. is called;

[Decision module]: This module calculates the decision result of each individual by setting a set of unified action criteria for each individual and introducing the idea of linear programming into the model, that is, the method of solving the optimal solution of the objective function under the constraints. ;

[Main function module]: This module is the entry point for the model to run and is responsible for

(1) Initialize the basic variables before the model runs, including control file variables, input and output file variables, and log file variables;

(2) Execute the simulation of each period in a loop, receive the simulation results of the previous period and transfer them to the simulation of the next period;

(3) Release the buffer and temporary files, save the program running log, and print the model running end information;

[File management module]: This module realizes the reading of all input files and control files. The model supports data files in xls, xlsx format and control files in txt format. This module is responsible for reading these data files and storing them in temporary In the buffer, when other modules need to obtain data, the file management module will query the temporary buffer, find the corresponding data and pass it to these modules;

[Interface module]: This module implements the loading of external link libraries. The model needs to call external operation libraries when calculating individual optimal decisions. These operation libraries cannot be directly connected to the model itself. The interface module constructs general access rules. The external library can be compatible with the model through the interface module, which is convenient for the expansion of the model;

The connection between the modules is as follows:

The decision-making module depends on the behavior module, the individual module and the government module, and the external library provides functional expansion support for the optimization module through the interface module;

The file management module is linked with the behavior module, individual module and government module to realize data transmission;

Behavior modules are aggregated in individual modules to realize the correspondence between behaviors and individuals;

The individual module is linked with the government module, and individual decision-making is subject to the government module's setting of the policy environment;

All other modules are aggregated in the main function, which together constitute the architecture of the entire model.

The objective functions in the decision module include:

【Profit income】: The profit function consists of total revenue minus total cost plus government subsidies and other revenue components;

Profit _t =Total Revenue-Total Cost+Subsidies+Other Income

It is formulated as: max1 _t =TR _t -TC _t +Sub _t +Ol _t

[Total revenue]: The total revenue TR _t is measured by the product of the output Q _t of all products produced in the year and the price P _t : TR _t = Q _t P _t

[Total cost]: The total cost TC _t includes the total variable cost VC _t and the total fixed cost FC _t ;

Calculated using the input-output method, that is, the product of output x _i , input-output coefficient α _{i, j} and factor price p _j to measure the current variable cost:

The total fixed cost refers to fixed assets such as factory buildings, machinery and equipment. This production factor is invested in one time and used in multiple periods. The cost calculation method is discounted to each year of the service life according to the total value of the purchase period, and the fixed asset purchase period is set. The total value is Fixed asset, the annual discount rate is r, and the service life is T, then the annual discounted cost of fixed assets is:

[Government subsidy]: There are two calculation forms for government subsidy Subsidies. When subsidy is made according to the results of production behavior, Sub ^out is the product of the change in the results of the out ^report during the project reporting period and the out ^base in the base period and the amount of subsidies; If the technology adoption is subsidized, Sub ^adoption calculates the product of adoption and subsidiies:

Sub ^out =subsidies*(out ^report -out ^base )

[Other income]: Other income is income other than production, expressed as the product of total labor OL _t and wage amount w _t : OI _t = OL _t w _t

To sum up, the objective function of individual profit maximization can be expressed as:

The constraints in the decision module are:

[Budget Constraint]: The budget constraint is that the individual sets a budget value in advance for the current year. The total production cost of the current year should be controlled within the budget value, including variable costs and fixed costs. The budget for each year is equal to the previous year's budget. Part of the total profit:

[Endowment Constraint]: Endowment constraint is the means of production, such as labor, machinery, land, etc., which are owned by the individual before the individual production begins. Let the initial endowment of each production factor of the individual be bj, and bj refers to the jth production factor, then It should be satisfied that the usage of each production factor is less than its endowment:

The specific process of the decision-making module is: the model reads the resource endowment file, production input and output file, and product price file of the behavior module, obtains the input-output coefficient of each production behavior, the resource endowment and product price of all individuals, and then calls the individual The module instantiates all individuals, calls the government module to instantiate the current policy environment, constructs the policy environment and resource endowment conditions for each individual's production decision, and defines the unified production goal of each individual, and finally imports these individuals into the linear programming function Calculate and output their optimal production behavior results in turn.

Example:

The specific embodiments of the method of the present invention will be further described below with reference to the accompanying drawings. The present invention provides a simulation model for individual decision-making, and the model running process is as follows:

1. The user sets the control parameters of the model operation according to the needs of use. These parameters include the total number of simulation periods of the model and the practical significance of each simulation period (such as "total simulation period = 5, one period = one year", which means that the model simulates reality 5 years), government subsidy method (result-oriented subsidy method or process-oriented subsidy method), and document storage path.

2. The user sets the input files according to the needs of use. These files include individual resource endowment files, production input and output files (input-output coefficients corresponding to each resource endowment for each production behavior), individual basic attribute files (each individual additional investment coefficient, age, gender, education level), product price document (product price per period), government subsidy document (subsidy standard for each period), document describing the technical characteristics used.

3. The model reads the input files and control parameters, calculates and obtains the optimal decision-making results of each individual according to its own resource endowment, and these results include which products to produce, which production technology to use, and the profit of each period. After the simulation of each simulation period, the model will summarize the decision results of all individuals in the current period into a file and output it.

4. After all simulation periods are completed, the model prints the end information and generates a log file (recording the overall situation of the model operation).

In the following, the individual decision-making simulation model is used to simulate the scenario in which the government implements subsidies for agricultural carbon emissions, and farmers make the allocation of production materials and the choice of production methods in order to maximize profits. The simulation environment includes 7 kinds of production crop options: wheat, japonica rice, indica rice, corn, soybean, rapeseed, cotton; covers 3 kinds of fertilization technology options: traditional fertilization technology, slow-release fertilizer technology, chemical fertilizer deep application technology; Consider two government subsidy methods : Subsidize according to the type of fertilization technology used by the actor, and subsidize according to the carbon emission reduction achieved in the production process of the actor; combine the 6 types of resources owned by the actor: seeds, fertilizers, pesticides, machinery, labor, and land for production decision making.

The specific implementation process is as follows:

First, the user sets the control parameters of the model operation as needed, and the interface is shown in Figure 3. The model simulates the individual decision-making behavior for 5 years from 2004 to 2008. "subsidyType" is used to control the choice of government subsidies, including two parameters: "adoption" and "outcome". "adoption" means the government subsidizes according to the type of technology used in the individual production process, and "outcome" means the government subsidizes according to the carbon emission reduction achieved in the individual production process. For ease of expression, the following introduces the decision-making method and decision-making results of the model design by taking the government's subsidy according to the type of technology used in the individual production process as an example. The data required to run the model is stored in "data/data01/".

The user then sets the input files needed for the model to run. Figure 4 shows all the sub-files in the data01 folder. The file "farm_endowment.csv" (Figure 5) stores the resource endowment data of a total of 60 individuals. Since different fertilization techniques will affect the input and output of various resource endowments, the production input and output data corresponding to the above three fertilization techniques are different, "input_output_tradition. 7) The "input_output_slow.csv" (Fig. 8) file saves the production input and output data of the traditional fertilization technology, the chemical fertilizer deep fertilization technology, and the slow-release fertilizer technology, respectively. The heterogeneity of individuals is reflected in the differences in the additional investment coefficient, age, gender, and education level of individuals in each period. The basic attribute data of individuals are stored in the "farm_parameters.csv" (Figure 9) file. The "carbon_price.csv" (Fig. 10) file is used to store the virtual carbon prices from 2004 to 2010, the "activity_price.csv" (Fig. 11) file records the transaction prices of 7 crops, and the "subsidy.csv" (Fig. 12) ) file records the subsidy amount given by the government according to the type of technology used by individuals, and the “carbon_reduce.csv” (Figure 13) file records the carbon emission reduction achieved by using the above three fertilization technologies in the production process of seven crops (in traditional The carbon emissions of fertilization technology are used as a reference).

Next, run the model. The model reads the control parameters and input files. The core of the optimization decision-making function lies in the optimization decision-making module. In this example, the individual's current profit is obtained by subtracting total costs from total revenue plus government subsidies. The total cost includes the total variable cost consisting of seeds, pesticides, and fertilizers, and the total fixed cost consisting of machinery, labor, and land. The optimal decision-making module aims at maximizing profit, and calculates the optimal production method selection and resource allocation plan for individuals using the above three fertilization technology scenarios. The total revenue is calculated by combining the output allocation data obtained by the linear programming algorithm and the given product price data. The amount of government subsidies is determined according to the adoption of individual technologies. The subsidy amount for traditional fertilization technology is 100 units, the subsidy amount for slow-release fertilizer technology is 10,000 units, and the subsidy amount for deep fertilizer application technology is 1,000 units. Figure 14, Figure 15, and Figure 16 show examples of the output results of the console: In this production cycle, if the individual numbered "4208070" uses traditional fertilization technology for production, he should choose to plant wheat, in terms of seeds, pesticides, and fertilizer costs. A total of 618.9 units of input are required, and the profit is about 1185.2 units; if an individual uses the slow-release fertilizer technology for production, he should choose to plant cotton, which requires a total of 223.7 units of investment in the cost of seeds, pesticides and fertilizers, and makes a profit of about 1058.8 units; if Individuals who use chemical fertilizer deep application technology for production should choose to plant cotton. In terms of seeds, pesticides, and fertilizer costs, a total of 223.7 units of input are required, and a profit of about 1,058.8 units. On this basis, combined with government subsidies, the total profits of the current three fertilization technology scenarios can be obtained respectively. Comparing these three total profit values, the optimal decision result is obtained. For example, the individual numbered "4208070" should use slow-release fertilizer technology to produce cotton in this production cycle, and the individual's total income at this time reaches 14029.6 units. The result is saved in the "result_5.csv" file (Figure 17), and after all simulation periods have been simulated, the model prints the end message and a log file is generated.

The embodiments of the present invention have been described above, but the scope of the present invention is not limited thereto, and the user can make various changes and implement them without departing from the gist of the present invention. within the scope of protection.

The invention as a whole solves the technical problems in the prior art, which limit the application of this type of simulation model due to the fact that the decision-making problems in the actual situation spread to all walks of life, the decision-making environment is complex and diverse, and the relevant influencing factors are numerous. Based on the algorithm, it simulates the decision-making behavior of actors to maximize their own utility or maximize profits under resource constraints. The application field of this type of model is broadened, and the built-in algorithm is suitable for solving decision-making problems in many fields such as agriculture and industry, and can maximize the value of existing data to assist individual decision-making. The application of this model will greatly improve the individual decision-making ability and the level of management decision-making.

Claims (4)

1. a simulation model of individual decision-making, is characterized in that, the model adopts modular programming, comprises behavior module, individual module, government module, decision-making module, main function module, file management module and interface module; [Behavior module]: The model obtains all production behaviors by reading the production input and output files, and constructs each behavior object through the behavior module. These behavior objects will be instantiated and called in the optimization decision module ; [Individual module]: The model obtains all individuals and their basic attributes by reading the individual basic attribute file, and constructs each individual object from these individuals through the individual module. These individual objects will be instantiated in the optimization decision module and created. is called; [Government Module]: The model reads government subsidy files and policy category parameters, and constructs government objects in the government module. At the same time, it completes the settings of subsidy methods, subsidy standards and demonstration individuals. The government objects will be instantiated in the optimization decision module and created. is called; [Decision module]: This module calculates the decision result of each individual by setting a set of unified action criteria for each individual and introducing the idea of linear programming into the model, that is, the method of solving the optimal solution of the objective function under the constraints. ; [Main function module]: This module is the entry point for the model to run and is responsible for (1) Initialize the basic variables before the model runs, including control file variables, input and output file variables, and log file variables; (2) Execute the simulation of each period in a loop, receive the simulation results of the previous period and transfer them to the simulation of the next period; (3) Release the buffer and temporary files, save the program running log, and print the model running end information; [File management module]: This module realizes the reading of all input files and control files. The model supports data files in xls, xlsx format and control files in txt format. This module is responsible for reading these data files and storing them in temporary In the buffer, when other modules need to obtain data, the file management module will query the temporary buffer, find the corresponding data and pass it to these modules; [Interface module]: This module implements the loading of external link libraries. The model needs to call external operation libraries when calculating individual optimal decisions. These operation libraries cannot be directly connected to the model itself. The interface module constructs general access rules. The external library can be compatible with the model through the interface module, which is convenient for the expansion of the model; The connection relationship between the modules is: A. The decision-making module depends on the behavior module, the individual module and the government module, and the external library provides functional expansion support for the optimization module through the interface module; B. The file management module is linked with the behavior module, individual module and government module to realize data transmission; C. The behavior module is aggregated in the individual module to realize the correspondence between behavior and individual; D. The individual module is linked with the government module, and individual decision-making is subject to the setting of the policy environment by the government module; E. All other modules are aggregated in the main function, which together constitute the architecture of the entire model. 2. the simulation model of a kind of individual decision-making according to claim 1, is characterized in that, the objective function in described decision-making module comprises: 【Profit income】: The profit function consists of total revenue minus total cost plus government subsidies and other revenue components; Profit _t =Total Revenue-Total Cost+Subsidies+Other Income It is formulated as: max∏ _t =TR _t -TC _t +Sub _t +OI _t [Total revenue]: The total revenue TR _t is measured by the product of the output Q _t of all products produced in the year and the price P _t : TR _t = Q _t P _t [Total cost]: The total cost TC _t includes the total variable cost VC _t and the total fixed cost FC _t ; Calculated using the input-output method, that is, the product of output x _i , input-output coefficients a _{i, j} and factor price p _j to measure the current variable cost:

The total fixed cost refers to fixed assets such as factory buildings, machinery and equipment. This production factor is invested in one time and used in multiple periods. The cost calculation method is discounted to each year of the service life according to the total value of the purchase period, and the fixed asset purchase period is set. The total value is Fixed asset, the annual discount rate is r, and the service life is T, then the annual discounted cost of fixed assets is:

[Government subsidy]: There are two calculation forms for government subsidy Subsidies. When subsidy is made according to the results of production behavior, Sub ^out is the product of the change in the results of the out ^report during the project reporting period and the out ^base in the base period and the amount of subsidies; If the technology adoption is subsidized, Sub ^adoption calculates the product of adoption and subsidies: Sub ^out =subsidies*(out ^report -out ^base )

[Other income]: Other income is income other than production, expressed as the product of total labor OL _t and wage amount w _t : OI _t = OL _t w _t To sum up, the objective function of individual profit maximization can be expressed as:

3. the simulation model of a kind of individual decision-making according to claim 1, is characterized in that, the constraint condition in described decision-making module is: [Budget Constraint]: The budget constraint is that the individual sets a budget value in advance for the current year. The total production cost of the current year should be controlled within the budget value, including variable costs and fixed costs. The budget for each year is equal to the previous year's budget. Part of the total profit:

【Endowment Constraint】: Endowment constraint is the means of production such as labor, machinery, land, etc. that are owned by the individual before the individual production begins. Let the initial endowment of each production factor of the individual be b _j , and b _j refers to the jth production factor , then the usage of each factor of production should be less than its endowment:

4. The simulation model of a kind of individual decision-making according to claim 1, is characterized in that, the concrete process of described decision-making module is: model reads behavior module resource endowment file, production input and output file, product price file, Obtain the input-output coefficients of various production behaviors, the resource endowments of all individuals and product prices, and then call the individual module to instantiate all individuals, call the government module to instantiate the current policy environment, and build the policy environment for each individual's production decisions, Resource endowment conditions, and at the same time define the unified production goal of each individual, and finally import these individuals into the linear programming function to calculate and output their optimal production behavior results in turn.

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